Use the following link to download the data used to render this graph in ASCII, comma-separated values format here: (CSV output)

Uses

This graph will give you an immediate view of the AS peering relationships
near the monitor. It is primarily useful to compare with the hosting
organization's own information about what ASes are providing transit for
your data, to see whether it matches what the Ark probes have discovered.
For example, one could see whether probes are travelling over
academic or commercial networks, and where those connect with each other.
It also gives the best sense of the monitor's relationship to the rest of
the Internet, by seeing how close it is to a Tier 1 or Tier 2 network.

Caveats

It is important to recognize that these graphs are meant to illuminate the
routing from a monitor, and not to show the volume of traffic normally
flowing on the links or their bandwidth. Because of this, an AS/IP that might
only be used for a small amount of actual traffic (but routes to a large
section of the address space) can seem disproportionately large on the
graph.

Characteristics of this graph

In this graph, we show the AS-level path dispersion, where all adjacent
hops within the same AS are collapsed into a single hop.
Typically, the first hop will be all one AS (ie, the local network that the
monitor is in), with the second or third hop starting to split into
different ASes as probes go to their destinations. This is seen as one
solid contiguous column with several smaller column segments to its right.

Background

(See the
Routed /24 Topology Dataset for more information. This applies
to all the dispersion graphs.)
Ark monitors collect data by sending scamper probes continuously to
destination IP addresses. Destinations are selected randomly from each
routed IPv4 /24 prefix on the Internet such that a random address in each
prefix is probed approximately every 48 hours (one probing cycle).
A single monitor won't probe all prefixes, but the prefixes it does probe
will be randomly distributed, which gives a good sample cross section of
the address space.
As each probe travels from the monitor to its final destination, it passes
through several IP addresses (ie, routers) which are owned by different
autonomous systems (ASes).

How This Graph was Created

(This applies to all the dispersion graphs.)

Data Processing

We first take the IP addresses found in each path and look up its
corresponding AS, creating a set of AS paths.
We use heuristics to infer any unknown
values in the IP and AS paths.
First, any range of unknown ASes whose previous and following hops have the
same value are all assumed to be within the same AS.
For example:

10 ?? ?? ?? 10

becomes

10 10 10 10 10

If there exists only one other known value between two neighboring values,
the unknown hop is assigned that value. This can often happen when
a router gives inconsistent responses, leaving an unknown hop some times
and returning valid data at other times.
For example, say there are only three paths:

10 20 30 40 50
10 20 30 42 52
10 ?? 30 45 55

From this, we infer the unknown hop in the third path, and end up with:

10 20 30 40 50
10 20 30 42 52
10 20 30 45 55

Graph Generation

Then, we merge all the paths together into a tree
structure to show how they disperse from the monitor as they go to
their destinations. Each column is broken into smaller column sections
based on the size of the previous hop.
The Y axis represents the number of probe paths that go through
a particular IP address or AS.
The graph we create is a tree (as opposed to the actual network, where
multiple paths can reconverge after diverging earlier), which allows IPs
and ASes to show up several times within the same column.

Coloring

Non-grayscale colors are assigned
to the ASes that show up the most, which are typically early in a path.
Less numerous ASes are assigned a dark grey, whereas black is used to
denote hops after the end of a particular path.
Any hops with an
unknown
IP or AS are denoted with '??' and
are colored a lighter grey.